Session F14: Sensing Chemical Spaces

Odor motion detection by an olfactory system aids navigation of complex odor plumes.

For many animals, survival depends on the ability to navigate odor plumes to their sources. This task is complicated by turbulent air motions, which break continuous odor streams emanating sources into disconnected odor patches swept by the wind. Animal studies have revealed a general strategy to navigate odor plumes: reorient upwind when the odor is present, but go crosswind or downwind when signals become sparse to regain contact with the plume. In this strategy, the olfactory system is used to detect the identity, intensity and arrival time of odor packets, while the main directional cue is wind direction. This is because gradients of odors, which can be detected by comparing odor intensity between the two antennae, tend to fluctuate in many directions.

We discovered that besides detecting the identity and intensity of odor packets, the Drosophila olfactory system also detects the direction of motion of odor packets. Simulations and theory show that odor motion provides a secondary directional cue, which points towards the center of the odor plume and therefore is complementary to the wind direction. Using a virtual reality setup to decouple wind from odor signal, we find that flies detect odor motion from the temporal correlations of the odor signal between its two antennae, in a computation similar to motion detection in vision. Manipulating spatio-temporal correlations in the virtual odor signal demonstrates that flies indeed exploit odor motion when navigating odor plumes. Thus, Drosophila can compute the direction of motion of odors independent of the wind, and they use this capability in natural plume navigation. This work suggests a novel role for previously observed bilateral signal processing in the olfactory circuit.   

Quantifying structure in immune receptor epitope maps

Adaptive immunity is driven by specific binding of hyper-variable receptors to diverse molecular targets. The many-to-many mapping between receptors and their epitope targets determines how the immune system senses threats, but an understanding of its global structure has remained elusive. In my talk I will introduce an analytical framework to quantify structure in recent high-throughput measurements of such maps. I will discuss how a combination of ideas from population genetics, molecular biophysics, and machine learning is enabling us decipher the probabilistic rules of the degenerate molecular binding code of the immune system.   

2022 Early Career Award for Biological Physics: Organization and encoding of memory in evolving environments

Biological systems, ranging from the brain to the immune system, store memory of molecular interactions to efficiently recognize and respond to stimuli. However, the strategies to encode memory can vary largely across different systems. In this talk, I will discuss how statistics and dynamics of stimuli should determine the optimal memory encoding strategies in biological networks. In particular, I will contrast the compartmentalized memory in the adaptive immune system, which primarily interacts with evolving pathogens, with the distributed memory in the olfactory cortex, which interacts with relatively static odor molecules. Focusing on the adaptive immune system, I will discuss how memory encoding could be understood in light of host-pathogen coevolution. Specifically, I will show that to achieve a long-term benefit for the host, immune memory should be actively regulated, with a preference for cross-reactive receptors with a moderate affinity against pathogens as opposed to high affinity receptors. Our theory also predicts that an organism’s life-expectancy should strongly impact the cross-reactivity of its immune memory, and we expect organisms with shorter life expectancy to carry more cross-reactive memory. This theoretical prediction can guide more comprehensive cross-species comparisons of immune systems, which is currently missing from immunological studies.   

Conventional and unconventional T cell receptor recognition

Human T cell analysis requires knowledge of the specificity (antigen target) and cellular functional profile. These analyses are complicated by the vast potential diversity of T cell receptors (estimated at >10⁶¹) and variation in presented target antigens determined by HLA. Here I will discuss approaches to deconstruct this complexity, utilizing TCR distance-based analysis and novel methods for integrating TCR sequence and single cell gene expression data. These approaches will be applied to studies of SARS-CoV-2 infection, influenza vaccination, and cancer to identify diverse T cell differentiation trajectories and clinically relevant associations with protected and susceptible phenotypes.